Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendments
The amendment and response filed on July 31, 2026, to the Non-Final Office Action dated May 5, 2026, has been entered. Claims 1-7 and 11-12 are amended. Claims 1 - 12 are pending in this application.
Response to Arguments
Applicant’s arguments and amendments, see pages 6-11, filed July 31, 2026, with respect to the 35 U.S.C. 101 rejections have been fully considered but are not persuasive. Applicant has amended independent claims 1-7 and 11-12 to now require or recite, in part, processor and memory to invoke the doctrine of “technical improvement” and the post-solution activity action of controlling, by the vehicle, a charging or discharging of the energy storage device. Firstly, the added processor and memory are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of ranking information based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component; and secondly the recitation of charging or discharging fails to convey that the claims implement a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim. See In re Sarkar, 200 USPQ 132 (CCPA 1978). The 35 U.S.C. § 101 rejection of claims 1-12 is maintained since the claims fail to add additional limitations that would amount to significantly more than the abstract idea .
Applicant’s arguments and amendments, see pages 6-11, filed July 31, 2026, with respect to the 35 U.S.C. § 103 rejection based on Taisuke Tsurutani (US-20200101865-A1), TOSHIHARU et al (JP-2012068075-A), and Kanada et al (US-20180208062-A1) have been considered but are not persuasive. The claims have been amended to recite hardware (processor and memory) and to recite the function of a charging or discharging cycle performed by the vehicle. The function of charging or discharging are taught by Tsurutani at Para. [0035]. The 35 U.S.C. § 103 rejection of claims 1-12 is maintained.
Claim Rejections – 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The determination of whether a claim recites patent ineligible subject matter is a 2 step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP 2106.04
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1)
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2)
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05
101 Analysis – Step 1
Claim 1 is directed to an information processing apparatus (i.e., a machine) for assessing the degradation of a vehicle battery. Therefore, claim 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c)
Independent claim 1 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
An information processing apparatus comprising:
a storage unit that stores history data relating to degradation of each of a plurality of energy storage devices;
an acquisition unit that acquires history data relating to degradation of an energy storage device mounted on a vehicle;
a similarity calculation unit that calculates similarity between the acquired history data and the stored history data [mental process/step];
an estimation unit that estimates a degradation index based on the stored history data which is similar to the acquired history data [mental process/step]; and
a transmission unit that transmits the estimated degradation index to the vehicle.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, calculating a “similarity between acquired history data and the stored” data and “estimates a degradation index based on stored history data…” in the context of this claim encompasses a person (driver) looking at data collected with similar data previously collected so as to form a simple judgement as to the degradation of an energy storage device like a battery. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.):
An information processing apparatus comprising:
a storage unit that stores history data relating to degradation of each of a plurality of energy storage devices [pre-solution activity (data gathering) using generic sensors];
an acquisition unit that acquires history data relating to degradation of an energy storage device mounted on a vehicle [pre-solution activity (data gathering) using generic sensors];
a similarity calculation unit that calculates similarity between the acquired history data and the stored history data [mental process/step];
an estimation unit that estimates a degradation index based on the stored history data which is similar to the acquired history data [mental process/step]; and
a transmission unit that transmits the estimated degradation index to the vehicle [Insignificant post-solution activity].
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of storing “history data relating to degradation of each of a plurality of energy storage devices …,” acquiring “history data relating to degradation of an energy storage device mounted on a vehicle …,” and transmitting “estimated degradation index to the vehicle …,” the examiner submits that these limitations are insignificant extra-solution activities that merely use a computer (electronic/vehicle controller) to perform the process. In particular, the collecting and inputting steps from the sensors and from an input source are recited at a high level of generality (i.e. as a general means of gathering vehicle and road condition data for use in the evaluating step), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Lastly, the various units such as “storage”, “acquisition”, and “transmission” are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of gathering energy storage data from a vehicle or a plurality of vehicles) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The claim as whole merely (implicitly) receives the data that is transmitted from the back-end server and does not perform any further functions. While the data is selected and transmitted, it is not transformed by any steps of the method, or used implement a specific control of the vehicle.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception. see MPEP § 2106.05. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a vehicle controller to perform the evaluating… amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic components like a computer cannot provide an inventive concept. And as discussed above, the additional limitations of storing “history data relating to degradation” of an energy device from a host vehicle or previous vehicles and transmitting “the estimated degradation index” to the host vehicle, the examiner submits that these limitations are insignificant extra-solution activities. In addition, these additional limitations (and the combination, thereof) amount to no more than what is well-understood, routine and conventional activity. Hence, the claim is not patent eligible.
Claim 2 recites an information processing apparatus that acquires additional data that relates to the “reliability of a degradation index” so as to use as a logical decision threshold to decide if the estimated “degradation index” is to be transmitted to the vehicle. Claim 2 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 3 recites an information processing apparatus that stores “ reliability of a degradation index” which then used to calculate weighting factors based on the similarity and the stored “ reliability” data so as to select an “energy storage device” that useful for using during the estimation of the degradation index. It merely consists of selecting data of an energy storage device as a function of similarity and reliability so as to estimate a degradation index so that the product of the calculation can be transmitted to a generic vehicle device such as a vehicle display . Claim 3 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 4 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as voltage. Claim 4 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 5 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as active material. Claim 5 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 6 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as manufacturers. Claim 6 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 7 recites an information processing apparatus that acquires additional data that relates to the position data of the vehicle in the form of “use region” data so as to use as a logical decision threshold to decide if the estimated “degradation index” is to be transmitted to the vehicle. Claim 7 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 8 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as temperature sections. Claim 8 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 9 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as use time for each SOC section. Claim 9 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 10 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as charge and discharge for each SOC section. Claim 10 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 11 recites an information processing apparatus that narrows the “similarity calculation” to certain energy storage device parameters such as transition of the degradation index and to determine a prediction of the index. Claim 11 does not recite additional elements that integrate the judicial exception into a practical application.
Claim 12 recites the same limitations as claim 1, these claims are likewise rejected as being directed to an abstract idea. While each of these limitations, as drafted, are a simple process/acts that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of by “information processing” device. Thus, the claim recites a mental process.
Thus, since independent claims 1 and 12 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that the independent claims are directed towards non-statutory subject matter.
As for dependent claims 2 -11 these claims include all the limitations of the independent claim from which they depend and therefore recite the same abstract idea. The claims also fail to add additional limitations that would amount to significantly more than the abstract idea. Therefore, the invention of claims 1-12 as a whole, considering all claim elements both individually and in combination, are not patent eligible under 35 USC §101.
Claim Rejections – 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2 and 4-12 are rejected under 35 U.S.C. 103 as being unpatentable over Taisuke Tsurutani (US-20200101865-A1)(“Tsurutani”) and TOSHIHARU et al (JP-2012068075-A)(“Toshiharu”), machine translation is attached.
As per claim 1, Tsurutani discloses an information processing apparatus (Figure 3) comprising:
a storage unit that stores history data relating to degradation of each of a plurality of energy storage devices (Tsurutani at Figure 8, server 501, and Para. [0100] discloses storing battery data of a plurality of vehicle:” center server 501 manages information relating to the battery mounted in the vehicle 10 on the basis of information transmitted from the plurality of vehicles 10 (communication devices).”);
an acquisition unit that acquires history data relating to degradation of an energy storage device mounted on a vehicle (Tsurutani at Figure 8, server 501, and Para. [0098] discloses the acquisition of data about a vehicle’s battery through an acquisition unit such as a wireless communication channel:” diagnosis system 500 is a battery control system that manages a deterioration state and the like of a battery 40 mounted in a vehicle 10. The diagnosis system 500 includes a plurality of vehicles 10 and a center server 501. The vehicle 10 and the center server 501 communicate with each other through a network NW. The network NW, for example, includes the Internet, a wide area network (WAN), a local area network (LAN), a provider device, a radio base station, and the like.”);
;
an estimation unit that estimates a degradation index based on the stored history data which is similar to the acquired history data (Tsurutani at Figure 8, server 501, and Para. [0101] disclosing estimating a degradation of a vehicle’s battery based on the stored information from a plurality of vehicles/batteries :” the center server 501 may receive information representing an output of the battery sensor 42 from the communication device of the vehicle 10 and estimate the deterioration state of the battery 40 on the basis of the information (the estimation unit 301).”); and
a transmission unit that transmits the estimated degradation index to the vehicle (Tsurutani at Figure 7, display 62, and Para. [0068] disclosing that a diagnostic device 100 transmit the degradation index to a vehicle display device:” the approval unit 303 causes the output unit 304 to output information representing a deterioration state of the battery 40 and an index value. When such information is received from the output unit 304, the display device 60 (the display control unit 64) causes the display unit 62 to display a notification image urging the execution of a capacity learning operation, a notification image representing a deterioration state of the battery 40, and a notification image representing an index value (reliability).”).
Tsurutani does not disclose, but Toshiharu discloses a similarity calculation unit that calculates similarity between the acquired history data and the stored history data (Toshiharu at Para. [0074] discloses that a battery (energy device) can be compared with historical performance data to determine a similarity that is indicative of the state of the battery:” the defect determination process part 340 will compare the past abnormal performance history map with a performance history map about the specified effective test item, will calculate the similarity for every module battery, and the similarity will be determined. It is determined whether (hereinafter referred to as module similarity) is equal to or greater than a predetermined threshold value. If the failure determination processing unit 340 determines that the module similarity is equal to or higher than the threshold value, the defect determination processing unit 340 further calculates the similarity for each unit cell, and the similarity (hereinafter referred to as unit cell similarity).”).
Toshiharu is considered to be analogous to the claimed invention because it is in the same field of systems which estimates the degradation of an energy storage device (battery) placed in a vehicle. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tsurutani further in view of Toshiharu to allow for finding the closest data from a database of historical data so as to identify a degradation of the battery in a vehicle. Motivation to do so would allow for reducing the use of computational resources and reducing the time needed to ascertain the level of deterioration of a first power storage element (battery) through a comparison with stored data of a plurality of power storage elements (batteries) (Toshiharu at Para. [0012]).
As per claim 2, Tsurutani and Toshiharu disclose an information processing apparatus according to claim1, wherein the acquisition unit acquires reliability of a degradation index of the energy storage device mounted on the vehicle (Tsurutani at Figure 6, reliability table, and Para. [0035] disclosing a reliability indication for the energy storage device (battery):” diagnosis device 100 estimates a deterioration state (for example, a state of health (SOH)) of the battery 40 on the basis of the output of the battery sensor 42. In addition, in a case in which the reliability of data (for example, ΔSOC) used for estimating a deterioration state is equal to or lower than a predetermined value, the diagnosis device 100 requests the charging control unit 210 of the charger 200 to perform a specific charging/discharging operation through the communication I/F 74 in accordance with a user's approval.”) and wherein the transmission unit transmits, when reliability of the degradation index estimated by the estimation unit is higher than the reliability acquired by the acquisition unit, the estimated degradation index to the vehicle (Tsuratani at Para. [0083] discloses using the estimated degradation index when the reliability is above a threshold value:” in a case in which a sum of the numbers of times of capacity learning exceeds a threshold, the reliability has a constant value. In a case in which the reliability (an index value) is configured to be identified using a sum of squares of ΔSOC of capacity learning data, a reliability identification table in which a sum of squares of ΔSOC and the reliability are associated with each other may be prepared.”).
As per claim 4, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the similarity calculation unit calculates similarity between the acquired history data and history data of an energy storage device (Toshiharu at Para. [0082] discloses calculating a similarity between the data records:” similarity calculation process is performed to calculate the similarity between the created performance history map and the past abnormal performance history map (step S1508).”), which has a use voltage in the same range as a use voltage of the energy storage device mounted on the vehicle, among the plurality of energy storage devices stored in the storage unit (Toshiharu at Para. [0028] discloses the use of electrical parameters like voltage as basis for the inspection or similarity:” an inspection regarding the performance and reliability of the unit cell (for example, the capacity and voltage of the unit cell, charging) (Inspection of current and voltage during discharging) (single cell inspection). Thereby, a single cell is completed and a single cell assembly process is complete | finished.”).
As per claim 5, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the similarity calculation unit calculates similarity between the acquired history data and history data of an energy storage device (Toshiharu at Para. [0074] discloses that the similarity calculation is based in historic and recently acquired data:” defect determination process part 340 will compare the past abnormal performance history map with a performance history map about the specified effective test item, will calculate the similarity for every module battery, and the similarity will be determined. It is determined whether (hereinafter referred to as module similarity) is equal to or greater than a predetermined threshold value.”), which has entirely or partially the same active material as an active material of the energy storage device mounted on the vehicle, among the plurality of energy storage devices stored in the storage unit (Toshiharu at Para. [0090] disclosing that the similarity can include the material of the energy storage device (battery):” operation data indicating the result of the test or inspection of the constituent material is stored for each material, for each single cell, and for each module battery, and the manufacturing information collection processing unit 310 supplies the manufacturing information to the battery manufacturing line 100 for manufacturing the module battery.”).
As per claim 6, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the similarity calculation unit calculates similarity between the acquired history data and history data of an energy storage device of the same manufacturer as the energy storage device mounted on the vehicle among the plurality of energy storage devices stored in the storage unit (Toshiharu at Para. [0090] discloses using manufacturing (manufacturer) information in the similarity calculation:” battery diagnostic device 300 for diagnosing a module battery is used to test or inspect the battery performance management storage database 320 for a single battery, a module battery, a single battery, or a material constituting the module battery before shipment. Manufacturing information showing results, module battery that is a good product out of manufacturing information, single battery, normal operation model value determined based on manufacturing information of material”.).
As per claim 7, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1,wherein the storage unit stores position data relating to a use region of each of the plurality of energy storage devices (Tsurutani at Para. [0070] discloses the use of position data for determining the degradation of the battery:” detection of the vehicle 10 to be positioned near the charger 200 using the position information, or acceptance of an operation input for charging start from a user.”), wherein the acquisition unit acquires position data related to a use region of the vehicle (Tsurutani at Para. [0062] discloses the use of position data such as location and the like:” includes position information representing a parked position of the vehicle 10 and information of a parking time of the vehicle 10 predicted on the basis of the running history.”), and
Tsurutani does not disclose, but Toshiharu discloses wherein the similarity calculation unit calculates similarity between the acquired history data and history data of an energy storage device entirely or partially in the same use region as a use region of the energy storage device mounted on the vehicle among the plurality of energy storage devices stored in the storage unit (Toshiharu at Para. [0090] discloses using attributes like environment of use which under the broadest reasonable interpretation is proxy for use region of the battery:” since the diagnostic result is received from the lithium ion battery diagnostic device 300, it can be used at the manufacturing stage environment and at the time of use. Therefore, it is possible to diagnose the performance of the battery in consideration of the environment.”).
Toshiharu is considered to be analogous to the claimed invention because it is in the same field of systems which estimates the degradation of an energy storage device (battery) placed in a vehicle. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tsurutani further in view of Toshiharu to allow for finding the closest data from a database of historical data so as to identify a degradation of the battery in a vehicle. Motivation to do so would allow for reducing the use of computational resources and reducing the time needed to ascertain the level of deterioration of a first power storage element (battery) through a comparison with stored data of a plurality of power storage elements (batteries) (Toshiharu at Para. [0012]).
As per claim 8, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the history data includes a use time in each of temperature sections for each of the temperature sections of the energy storage device (Tsurutani at Para. [0104] discloses using temperature and time as basis for determining a degradation index:” may receive information relating to the deterioration state of the battery (information or an index value representing a deterioration state) and use status information (a battery temperature, a running load, an average SOC, the number of times of charging, and the like) from each vehicle 10 and calculate and manage an average value of each value thereof for the plurality of vehicles 10. The vehicle 10 may receive an average value calculated by the center server 501 and display the received average value and information relating to the battery of the own vehicle on the display unit 62 in association with each other.”).
As per claim 9, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the history data includes a use time in each of SOC sections for each of the SOC sections of the energy storage device (Tsurutani at Para. [0032] discloses including SOC sections of the energy storage device:” battery VCU control unit calculates a state of charge (SOC; a battery charging rate) of the battery 40 on the basis of an output of the battery sensor 42 mounted in the battery 40 and outputs the calculated SOC to the VCU 34 and the diagnosis device 100.”).
As per claim 10, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1,wherein the history data includes an accumulated charge-discharge amount in each of SOC sections for each of the SOC sections of the energy storage device (Toshiharu at Para. [0031] disclosing the maintaining history data of the charge-discharge cycle:” controller C has a counter that counts the number of times the unit cell is charged or discharged, and a timer that measures an elapsed time since the module battery is shipped. Further, the controller C is similar to the above-described inspection data, electrode manufacturing data, single cell QC inspection data, single cell product inspection data, module battery QC inspection data, and module battery product inspection data at the present time (for example, charging time”.).
As per claim 11, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the estimation unit predicts future degradation estimation of the energy storage device based on the estimated degradation index or transition of the degradation index, and wherein the transmission unit transmits the prediction of the degradation estimation to the vehicle (Tsurutani at Para. [0088] discloses predicting a next running and when a future degradation estimation is to be performed:” time information 405 represents a current time and a predicted time for the next running It can be indirectly notified to a user that a predetermined time (for example, six hours) for performing a capacity learning operation can be secured from the current time and the predicted time for the next running In addition, a notification indicating that a predetermined time is required for a capacity learning operation may be performed together with the time information 405 or instead of the time information 405.”) .
As per claim 12, Tsurutani discloses an information processing method (Figure 4) comprising:
storing history data relating to degradation of each of a plurality of energy storage devices (Tsurutani at Figure 8, server 501, and Para. [0100] discloses storing battery data of a plurality of vehicle:” center server 501 manages information relating to the battery mounted in the vehicle 10 on the basis of information transmitted from the plurality of vehicles 10 (communication devices).”);
acquiring history data relating to degradation of an energy storage device mounted on a vehicle (Tsurutani at Figure 8, server 501, and Para. [0098] discloses the acquisition of data about a vehicle’s battery through an acquisition unit such as a wireless communication channel:” diagnosis system 500 is a battery control system that manages a deterioration state and the like of a battery 40 mounted in a vehicle 10. The diagnosis system 500 includes a plurality of vehicles 10 and a center server 501. The vehicle 10 and the center server 501 communicate with each other through a network NW. The network NW, for example, includes the Internet, a wide area network (WAN), a local area network (LAN), a provider device, a radio base station, and the like.”);
;
estimating a degradation index based on the stored history data which is similar to the acquired history data (Tsurutani at Figure 8, server 501, and Para. [0101] disclosing estimating a degradation of a vehicle’s battery based on the stored information from a plurality of vehicles/batteries :” the center server 501 may receive information representing an output of the battery sensor 42 from the communication device of the vehicle 10 and estimate the deterioration state of the battery 40 on the basis of the information (the estimation unit 301).”); and
transmitting the estimated degradation index to the vehicle (Tsurutani at Figure 7, display 62, and Para. [0068] disclosing that a diagnostic device 100 transmit the degradation index to a vehicle display device:” the approval unit 303 causes the output unit 304 to output information representing a deterioration state of the battery 40 and an index value. When such information is received from the output unit 304, the display device 60 (the display control unit 64) causes the display unit 62 to display a notification image urging the execution of a capacity learning operation, a notification image representing a deterioration state of the battery 40, and a notification image representing an index value (reliability).”).
Tsurutani does not disclose, but Toshiharu discloses calculating a similarity between the acquired history data and the stored history data (Toshiharu at Para. [0074] discloses that a battery (energy device) can be compared with historical performance data to determine a similarity that is indicative of the state of the battery:” the defect determination process part 340 will compare the past abnormal performance history map with a performance history map about the specified effective test item, will calculate the similarity for every module battery, and the similarity will be determined. It is determined whether (hereinafter referred to as module similarity) is equal to or greater than a predetermined threshold value. If the failure determination processing unit 340 determines that the module similarity is equal to or higher than the threshold value, the defect determination processing unit 340 further calculates the similarity for each unit cell, and the similarity (hereinafter referred to as unit cell similarity).”).
Toshiharu is considered to be analogous to the claimed invention because it is in the same field of systems which estimates the degradation of an energy storage device (battery) placed in a vehicle. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Tsurutani further in view of Toshiharu to allow for finding the closest data from a database of historical data so as to identify a degradation of the battery in a vehicle. Motivation to do so would allow for reducing the use of computational resources and reducing the time needed to ascertain the level of deterioration of a first power storage element (battery) through a comparison with stored data of a plurality of power storage elements (batteries) (Toshiharu at Para. [0012]).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Tsurutani and Toshiharu as applied to claim 1 above, and further in view of Kanada et al (US-20180208062-A1)(“Kanada”).
As per claim 3, Tsurutani and Toshiharu disclose an information processing apparatus according to claim 1, wherein the storage unit stores reliability of a degradation index of each of the plurality of energy storage devices (Tsurutani at Para. [0082] disclosing that the reliability of degradation index is acquired presumable from memory 310:” a reliability determination table is a table in which a sum of the numbers of times of capacity learning and reliability of data used for estimating a deterioration state are associated with each other. The number of times of capacity learning is a value (a total number) acquired by counting the number of times of capacity learning for a latest predetermined period. The reliability is a value (a value represented as a percentage) set in correspondence with the number of times of capacity learning.”), wherein the information processing apparatus includes:
Tsurutani and Toshiharu do not disclose, but Kanada discloses a weighting calculation unit that calculates a weighting based on the calculated similarity and the stored reliability (Kanada at Figure 8, weighting of a record, and Para. [0073] discloses assigning weights to records based on the similarity or attributes such vehicle and battery type and the like:” weighting can be performed based on identification information (vehicle ID) of the vehicles 1, 2 transmitted from the vehicles 1, 2 to the server 300.”); and
Tsurutani and Toshiharu do not disclose, but Kanada discloses a selection unit that selects an energy storage device from among the plurality of energy storage devices based on the calculated weighting, and wherein the estimation unit estimates a degradation index based on history data of the selected energy storage device (Kanada at Figures 8-9 and Para. [0080] discloses selecting of records as weighted by the server that best fits a particular set of attributes:” Tsurutani and Toshiharu do not disclose, but Kanada discloses … it is preferable for the server 300 to perform weighting as described with reference to FIG. 8 on the selected record d.”).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the system for estimating the deterioration state of batteries as taught by Tsurutani and modified by Toshiharu with the weighting of records as taught by Kanada with a reasonable expectation of success in order for the one or more records relating to the degradation to a plurality of energy storage devices can be weighted for quick identification. The teaching suggestion/motivation to combine is that by recording weights to each record in the degradation database, estimation accuracy of the deteriorated state of the secondary battery can be improved as taught by Kanada in Paras. [0014] -[0016].
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chou; Chung-Jen et al. US 20130166234 A1 METHOD FOR ESTIMATING BATTERY DEGRADATION;
Shimizu; Takahiro US 10408887 B2 Method for estimating degradation of rechargeable battery, degradation estimation circuit, electronic apparatus and vehicle including same;
Kubotani; Tsuyoshi et al. US 12571850 B2 Storage battery management device, storage battery system, and storage battery management method.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ELLIS B. RAMIREZ/Primary Examiner, Art Unit 3658
